The Research of Urban Rail Transit Sectional Passenger Flow Prediction Method

Abstract

This paper studies the short-term prediction methods of sectional passenger flow, and selects BP neural network combined with the characteristics of sectional passenger flow itself. With a case study, we design three different schemes. We use Matlab to realize the prediction of the sectional passenger flow of the Beijing subway Line 2 and make comparative analysis. The empirical research shows that combining data characteristics of sectional passenger flow with the BP neural network have good prediction accuracy.

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Q. Li, Y. Qin, Z. Wang, Z. Zhao, M. Zhan, Y. Liu and Z. Li, "The Research of Urban Rail Transit Sectional Passenger Flow Prediction Method," Journal of Intelligent Learning Systems and Applications, Vol. 5 No. 4, 2013, pp. 227-231. doi: 10.4236/jilsa.2013.54026.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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http://dx.doi.org/10.1038/323533a0
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